Abstract The purpose of this study is to explore the application value of positioning based on the treatment couch height in radiotherapy for left-sided breast cancer. Sixty patients who had undergone radical mastectomy for left breast cancer were selected, with each patient undergoing positioning based on the treatment couch height (couch height group) and positioning based on the reference marking lines (reference line group), to obtain the corresponding positioning errors. Meanwhile, 20 of 60 patients were randomly selected, and the planning system was used to simulate the changes in radiation doses in planning target volume (PTV) and organs at risk (OAR) along with the changes in positioning errors in dorsal (increasing couch height) and ventral (decreasing couch height), respectively. Compared with the original plan, when the positioning error in the dorsal direction reached 3mm, Dmean, V30, and V20 in The ipsilateral lung were increased by 35.12%, 16.35%, and 10.6% respectively, and V50 in PTV was decreased by 0.99% (all p < 0.05); when the positioning error in the ventral direction reached 1.5 mm, V50, V48, and V45 were decreased by 2.07%, 0.58%, and 0.14% respectively. The homogeneity index (HI) was increased by 14.28% (all p < 0.05). There was a statistically significant difference in the positioning errors in the ventral-dorsal directions between the couch height group (0.16±0.14 cm) and reference line group (0.36±0.25 cm) (p < 0.05); the percentages of the absolute positioning errors within 1.5mm and 3mm were 52.4%, 88.7% respectively in the couch height group and 29.8%, 54.4% respectively in the reference line group, (all p < 0.05). Dorsal positioning errors greater than 3 mm significantly worsen the dose distribution for both the PTV and OAR, while positioning based on the treatment couch height keeps 88.7% of positioning errors within 3 mm; ventral positioning errors greater than 1.5 mm result in significant changes in the dose within the PTV. Compared to the reference line group, positioning based on the treatment couch height controls 52.4% of positioning errors within 1.5 mm. Therefore, couch height positioning demonstrates greater advantages in managing ventral-dorsal positioning errors. This study provides a reference for clinical positioning in postoperative adjuvant radiotherapy of breast cancer. Keywords: Breast cancer radiotherapy, Positioning error, Treatment couch height, Dose distribution
Abstract Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow imaging speed, resulting in low patient throughput and compromised clinical diagnostic quality. The limited temporal resolution also causes patient discomfort and introduces artifacts in the images, further diminishing their overall quality and diagnostic value. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have so far not been made publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. The ‘CMRxRecon’ dataset contains raw k-space data and auto-calibration lines. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community.
The ability of extracellular vesicles (EVs) to regulate a broad range of cellular processes has recently been used to treat diseases. Growing evidence indicates that EVs play a cardioprotective role in heart disease by activating beneficial signaling pathways. Multiple functional components of EVs and intracellular molecular mechanisms are involved in the process. To overcome the shortcomings of native EVs such as their heterogeneity and limited tropism, a series of engineering approaches has been developed to improve the therapeutic efficiency of EVs. In this review, we present an overview of the research and future directions for EVs-based cardiac therapies with an emphasis on EVs-mediated delivery of therapeutic agents. The advantages and limitations of various modification strategies are discussed, and possible opportunities for improvement are proposed. An in-depth understanding of the endogenous properties of EVs and EVs engineering strategies could lead to a promising cell-free therapy for cardiac repair.
Abstract Metabolic diseases, including obesity, diabetes, and nonalcoholic fatty liver disease (NAFLD), are rising in both incidence and prevalence and remain a major global health and socioeconomic burden in the twenty-first century. Despite an increasing understanding of these diseases, the lack of effective treatments remains an ongoing challenge. Mitochondria are key players in intracellular energy production, calcium homeostasis, signaling, and apoptosis. Emerging evidence shows that mitochondrial dysfunction participates in the pathogeneses of metabolic diseases. Exogenous supplementation with healthy mitochondria is emerging as a promising therapeutic approach to treating these diseases. This article reviews recent advances in the use of mitochondrial transplantation therapy (MRT) in such treatment.
Protein S-100B is a specific nutritious protein in nervous tissue.Cerebral damage induces much release of S-100B from spongiocyte,which exerts toxic effects on nervous tissue.S-100B is a high sensitive and specific marker of reflecting brain injury. Its serum peak level and duration are positively related to the degree of brain injury.Serum S-100B is detected easily and quickly in clinic.Therefore,S-100B is quite possibly become a biochemical marker to assess the degree of brain damage and the prognosis of nervous tissue.
Three kinds of commonly vertical flow constructed wetlands substrates,such as biological ceramsite,anthracite and zeolite,were selected.After the MgCl2 and FeCl3with the metal molar ratio(M2+: M3+) of 2:1were co-precipitated in alkaline conditions to synthesize MgFe-LDHs,the synthesized MgFe-LDHs were in-situ coated on the surface of three kinds of substrates.The simulated substrates test columns were constructed to treat the contaminated lake water using formerly substrates before and after modification.The method of synthesized LDHs being in-situ coated on substrates of vertical flow constructed wetland was feasible.After the modification,the purification effects of CODCr,ammonia nitrogen and total phosphorus were improved by various degrees.Among them,the modified anthracite had optimal performance with average removal efficiencies of CODCr,ammonia nitrogen and total phosphorus more than 80%,60% and 90%,respectively.
Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a limitation of CMR is its slow imaging speed, which causes patient discomfort and introduces artifacts in the images. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have not been publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. Manual segmentations of the myocardium and chambers of all the subjects are also provided within the dataset. Scripts of state-of-the-art reconstruction algorithms were also provided as a point of reference. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community. Researchers can access the dataset at https://www.synapse.org/#!Synapse:syn51471091/wiki/.
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